Journal ArticleDOI
Digital twin-driven product design, manufacturing and service with big data
TLDR
In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed, and three cases are given to illustrate the future applications of digital twin in three phases of a product respectively.Abstract:
Nowadays, along with the application of new-generation information technologies in industry and manufacturing, the big data-driven manufacturing era is coming. However, although various big data in the entire product lifecycle, including product design, manufacturing, and service, can be obtained, it can be found that the current research on product lifecycle data mainly focuses on physical products rather than virtual models. Besides, due to the lack of convergence between product physical and virtual space, the data in product lifecycle is isolated, fragmented, and stagnant, which is useless for manufacturing enterprises. These problems lead to low level of efficiency, intelligence, sustainability in product design, manufacturing, and service phases. However, physical product data, virtual product data, and connected data that tie physical and virtual product are needed to support product design, manufacturing, and service. Therefore, how to generate and use converged cyber-physical data to better serve product lifecycle, so as to drive product design, manufacturing, and service to be more efficient, smart, and sustainable, is emphasized and investigated based on our previous study on big data in product lifecycle management. In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed. The detailed application methods and frameworks of digital twin-driven product design, manufacturing, and service are investigated. Furthermore, three cases are given to illustrate the future applications of digital twin in the three phases of a product respectively.read more
Citations
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Proceedings ArticleDOI
Optimal RUL Estimation: A State-of-Art Digital Twin Application
TL;DR: The Long-Short Term Memory (LSTM) Recurrent Neural Network (RNN) technique is extended to generate RUL prediction within a digital twin framework as a means of synchronization with changing operational states to demonstrate wide applicability to various industries where event data is scarce for the application of only data-driven techniques.
Book ChapterDOI
Digital Twin with a Perspective from Manufacturing Industry
TL;DR: A specific view from semiconductor manufacturing is provided to see why DT is necessary, and several research opportunities are presented as inspirations for future work.
Journal ArticleDOI
Role of smart materials and digital twin (DT) for the adoption of electric vehicles in India
Shashi Bahl,Sayed Suhaib Kamran,Abid Haleem,Shashi Bahl,Mohd Javaid,Devaki Nandan,Ajay Singh Verma +6 more
TL;DR: In this paper, the authors have discussed the complexities regarding the repair and maintenance of EVs and aims to ease the process to ensure a bright future for the EV industry in the Indian markets.
Journal ArticleDOI
Exploring the Potential of Digital Twin-Driven Design of Aero-Engine Structures
TL;DR: How data from production are used today, what issues prevents such data from being exploited in the design phase, and how they potentially could be used for design purposes in the future are explored.
Journal ArticleDOI
Simulation Models of Production Plants as a Tool for Implementation of the Digital Twin Concept into Production
TL;DR: This dissertation aims to provide a history of Czech production technology and management from 1989 to 2002, a period chosen in order to explore its roots as well as specific cases up to and including the year in which the Czechoslovakia collapsed.
References
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Journal ArticleDOI
Internet of Things in Industries: A Survey
Li Da Xu,Wu He,Shancang Li +2 more
TL;DR: This review paper summarizes the current state-of-the-art IoT in industries systematically and identifies research trends and challenges.
Proceedings ArticleDOI
The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
TL;DR: In this article, the Digital Twin system integrates ultra-high fidelity simulation with the vehicle s on-board integrated vehicle health management system, maintenance history and all available historical and fleet data to enable unprecedented levels of safety and reliability.
Journal ArticleDOI
Reengineering Aircraft Structural Life Prediction Using a Digital Twin
TL;DR: A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented and the technical challenges to developing and deploying a Digital Twin are discussed.
Book ChapterDOI
Digital Twin—The Simulation Aspect
Stefan Boschert,Roland Rosen +1 more
TL;DR: This chapter focuses on the simulation aspects of the Digital Twin, where simulation merges the physical and virtual world in all life cycle phases and enables the users to master the complexity of mechatronic systems.
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